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Precipitation and Attenuation Estimates from a High Resolution Weather Radar Network (PATTERN)

Subject Area Atmospheric Science
Term from 2010 to 2015
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 168167151
 
Final Report Year 2017

Final Report Abstract

In the framework of the project "Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network" (PATTERN) the applicability and benefit of a network of low-cost X-band radars as useful supplement to larger scale radars has been demonstrated for highresolution precipitation observations. A network of four High-Resolution Weather Radars (HRWR) operating in the X-band frequency range has been set-up in Northern Germany and provides a multi-year dataset of continuous measurements since January 2012. Radars do not measure precipitation directly, they measure reflectivity. Therefore, raw data does not only contain signals from rain drops but also background noise and signals from obstacles along the radar beam (e.g. houses, trees, other emitters), so called clutter. A chain of algorithms has been developed and tailored to the specific requirements of the HRWR systems in order to estimate background noise level and identify clutter. Besides common clutter algorithms, novel techniques are developed based on unique features of high temporal resolution of 30 s and large areas covered by multiple radars. It turned out that the clutter algorithm based on multiple coverage within the network is the most efficient one and outperforms classic methods for single radars. A comparison with established C-band radar from the German Meteorological Service (DWD) indicates very good agreement of both systems with a probability of detection of more than 90% and a false alarm ratio of less than 10%. A large source of error in X-band radar systems is the high influence of attenuation due to liquid water. Therefore, a method for attenuation correction using measurements from the DWD C- band radar that are less affected by attenuation has been developed. This method is applicable for single as well as networks of X-band radars and shows very promising results. The datasets obtained within the PATTERN project serves as basis for a DFG funded fellowship entitled Improving Hydrometeorological Forecasts Using High-Resolution X-Band Radars (HyFoX). The aim of HyFoX is to investigate the influence and benefit of highresolution precipitation data on rainfall-runoff simulations in different kinds of environment (flat rural, flat urban and mountainous urban). Future applications of the network to analyze urban flash flood risks are envisioned. An article about possible application of HRWR networks, like the one established within the PATTERN project, for severe weather warnings is published on www.planeterde.de (http://www.planeterde.de/wissen/unwetterwarnung-fuer-einzelne-strassenzuege/).

Publications

  • 2012: Precipitation and Attenuation Estimates from a High Resolution Weather Radar Network (PATTERN) – Design of the Experiment, Proc. of 7th European Conference on Radar in Meteorology and Hydrology, Toulouse, France, 25th-29th June 2012
    Lengfeld, K., Clemens, M., Feiertag, N. and F. Ament
  • 2013: PATTERN: Advantages of High-Resolution Weather Radar Networks, Proc. of AMS 36th Conference on Radar Meteorology, Breckenridge, CO, USA
    Lengfeld, K., Clemens, M., Münster, H. and F. Ament
  • 2014: Performance of High- Resolution X-band Weather Radar Networks – the PATTERN Example, Atmos. Meas. Tech., Vol.7(12), pp. 4151-4166
    Lengfeld, K., Clemens, M., Münster, H. and F. Ament
    (See online at https://doi.org/10.5194/amt-7-4151-2014)
  • 2015: A Novel Approach for Absolute Radar Calibration, Atmos. Meas. Techn. Discuss., Vol.8, pp. 1671-1695
    Merker, C., Peters G., Clemens, M., Lengfeld, K., and F. Ament
    (See online at https://dx.doi.org/10.5194/amtd-8-1671-2015)
  • 2016: A Simple Method for Attenuation Correction in Local X-Band Radar Measurements Using C-Band Radar Data. J. Atmos. Oceanic Technol., 33(11), 2315-2329
    Lengfeld, K., Clemens, M., Merker, C., Münster, H., and F. Ament
    (See online at https://doi.org/10.1175/JTECH-D-15-0091.1)
 
 

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